Top Interview Questions for ML Intern
An ML intern is someone who works alongside machine learning engineers to develop artificial intelligence programs.
According to reports, 65% of all companies are planning to adopt machine learning to help them with faster and more efficient decision-making tasks.
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Hard Skills
Use these questions to identify a candidate’s technical knowledge and abilities
Soft Skills
Use these questions to assess a candidate’s personality traits and cognitive skills
What to look for while interviewing for an ML Intern?
Since the required skills for an ML intern require experience in data analysis and feature engineering, ML algorithm selection among others. Therefore, look for a candidate who has knowledge of all these.
Here are some of the in-demand skills for an ML Intern
Role-specific skills to look for: Concepts of computer science and software engineering, data analysis and feature engineering, metrics involved in ML, ML algorithm selection, and cross-validation, and Math and Statistics
Soft skills to look for time management, problem-solving, communication, curiosity to learn, and teamwork.
Pro Tip: Always screen before you interview. Use Online Assessment to screen applicants for an ML intern position before blocking your time for an in-person interview.
Questions to ask while interviewing an ML Intern
We have compiled a set of questions with the help of 70+ hiring managers at different organizations.
Top Role-based interview questions for ML Intern
What is more important between model accuracy and model performance, according to you?
Purpose of this interview question:
This question can be asked to determine if the candidate chooses the accuracy or performance of a model.
What to listen for:
- Candidates must give the reason of their choice, while top candidates would usually explain how model accuracy is a subset of model performance and how they both are important.
How would you design an application for loan prediction?
Purpose of this interview question:
By asking this question, the interviewer can test how well the candidate can apply their knowledge and skills of machine learning to design something new.
What to listen for:
- Top candidates would list out the procedure of designing software while applying their ideas and machine learning concepts to them.
Can you give examples of how you use Machine learning in daily life?
Purpose of this interview question:
This question can be asked to analyze the candidate’s awareness and analysis of machine learning in their daily life.
What to listen for:
- An ideal candidate would list out the daily live usage examples of ML and show evidence of curiosity.
How to screen ML Intern for soft skills?
Has there been any time where you had to take the lead in a group setting to overcome an obstacle?
Purpose of this interview question:
This question can be asked to gauge a candidate’s problem-solving and collaborative skills.
What to listen for:
- Top candidates would talk about their experience with working in a team environment.
What are you planning to do after completing this internship?
Purpose of this interview question:
The question is designed to understand if the candidate has the potential to work for your company long-term.
What to listen for:
- Listen to whether the candidate has the potential for continued work at the company.
What are your work expectations and what do you expect to gain from this internship?
Purpose of this interview question:
This question can help in revealing what a candidate expects to get out of this position and what they think the work will involve.
What to listen for:
- An ideal candidate would talk about their goals which they expect to achieve.
Start Optimizing your ML Intern Hiring today
Find and hire talent with confidence. If your candidate doesn’t know the answer to the above questions and you’re hiring for an ML Intern position, then they’re probably not a great fit.
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